Network analysis has been applied in many ecological and behavioral contexts to investigate systems of complex interactions. Its broad applicability is due in part to the generality of what constitutes a network—a set of objects (referred to as nodes) that are linked by some sort of connection (termed edges). Until recently, however, network analyses were largely descriptive in nature, which limited their utility. Statistical advances now allow networks to be modeled, which has expanded the capabilities of network analysis for hypothesis testing. One such advance is exponential random graph models (ERGMs). Developed for the social sciences, ERGMs analyze how network structures (i.e., configurations of edges) and attributes of nodes and edges affect the formation of edges. This allows practitioners to explore how different mechanisms shape networks of interest. In this dissertation, we introduce ERGMs to ecologists and animal behaviorists, highlight their advantages and applications, and demonstrate some of their uses in a series of case studies of social foraging dynamics in a community of songbirds. Using radio frequency identification technology, we monitored behavior at bird feeders in east-central Illinois over a two-year period to develop a unique dataset of foraging activity and social interactions. Data were then used to build networks that were analyzed using ERGMs in the following chapters.
In chapter 2, we explored how urbanization affects species interactions within social foraging networks at bird feeders. Anthropogenic change reduces species richness and size of mixed-species foraging flocks, so we expected urbanization would reduce the number of species at feeders and simplify social foraging network structure. Though species richness declined with urbanization, complexity of social foraging networks did not. Interspecific foraging declined as species that facilitate the formation of mixed-species foraging flocks were extirpated by urbanization, but reductions in interspecific foraging were compensated for by increases in intraspecific foraging among introduced species. This is the first study to demonstrate how urbanization shapes interactions in mixed-species foraging assemblages.
In chapter 3, we examined the role of interspecific interactions in shaping daily patterns of foraging activity of small birds in temperate winters. Theoretical investigations of this system are a classic case of modeling tradeoffs—in this instance between the risks of starvation and predation. However, these models do not account for interspecific variation in predator behavior or prey responses, though interactions among prey and between predators and prey are known to affect foraging behavior. We did not observe any influence of interspecific social foraging on temporal feeding patterns, but species varied in terms of daily foraging activity. We hypothesized that differences in vulnerability to predation due to variation in species-specific predator/prey relationships produced these patterns.
In chapter 4, we investigated how social dynamics can be modified by disease and how these changes can in turn affect disease transmission. We compared foraging behaviors of house finches (Haemorhous mexicanus) captured with and without a bacterial disease (mycoplasmal conjunctivitis) to determine if infected birds differed in foraging activity, patterns of association with heterospecifics and conspecifics, and sociality (i.e., number of foraging partners). Infected house finches were more likely to visit feeders and forage with other birds. These behavioral changes were likely the result of the disease but also increased the risk of disease transmission to healthy birds, particularly because of the possibility of indirect transmission at contaminated bird feeders.
We have demonstrated that ERGMs are a useful tool for studying mechanisms underlying complex biological networks and hope our work stimulates future use of ERGMs in ecological and behavioral contexts.